1. Technical Field
The present disclosure relates to the field of digital video analysis and encoding, particularly a method of detecting long shots in sports video.
2. Background
Watching sports video is a popular pastime for many people. Digital transmissions of sports video can be viewed on televisions directly or through set-top boxes, or on other devices such as personal computers, tablet computers, smartphones, mobile devices, gaming consoles, and/or other equipment. Digital recordings of sports video can be viewed on the same devices and viewing the digital recordings can begin at the start of a recorded event or midway through the event.
Automatic parsing of sports video based on visual and/or cinematographic cues can be used to identify segments of potential interest to a viewer, and/or points at which video on demand playback can begin. Visual cues, such as long shots, medium shots and close up shots, can be used to identify segments of the video where on-field events are occurring, or to distinguish on-field events from close up views of players, referees, balls, logos, or other items. Long shots frequently provide coverage of large areas of a playing surface, such as a playing field or court, and frequently identify periods of time during which activity on the field is at a maximum. Extended periods of play can comprise a sequence of long shots followed by medium and/or close up shots which signify the end of a play or highlight the contributions of key players. Detection of long shots can also aid in automatically identifying highlights from the video, and/or automatically summarizing video.
Some methods of detecting long shots have been developed. However, most existing methods require training time and cannot immediately identify long shots based on a single frame of video. For example, some methods create hue histograms from randomly selected frames over a period of time, and then identify peaks and thresholds from the histogram. These methods require time for their model to be trained at the beginning of a sports video, and the training can be impeded when non-sports video is interspersed with the sports video, such as commercials or pre-game analysis, or if portions of the field are covered with statistics, logos or other graphics. In other methods, the color of a playing surface is learned at the beginning of a sports video, but the method can need time to learn the color of the playing surface before the long shot detection algorithm can begin. In still other methods, the color of the playing surface must be preidentified, and/or compares the color of the playing surface to a reference model.